Abstract:

This thesis deals with flux estimators for speed-sensorless induction motor drives. To enhance the stability and the performance of state-of-the-art sensorless drives, new flux estimator designs based on the standard motor model are proposed. Theoretical and experimental research methods are both used. The dynamics and stability of flux estimators are analyzed using linearized models, and the effects of parameter errors are investigated using steady-state relations. Performance is evaluated using computer simulations and laboratory experiments. It was found that most sensorless flux estimation methods proposed in the literature have an unstable operating region at low speeds (typically in the regenerating mode) and that the damping at high speeds may be insufficient. A new stable design of the speed-adaptive full-order flux observer is proposed: the observer gain is designed especially for nominal and high-speed operation, while the low-speed operation is stabilized by modifying the speed-adaptation law. Compared to estimators proposed in the literature, the effects of parameter errors on the proposed observer design are shown to be small. To further improve the robustness, the speed-adaptive observer is enhanced with a low-frequency signal-injection method, allowing long-term zero-frequency operation under rated load torque. Furthermore, a computationally efficient version of a voltage-model-based flux estimator and two computationally efficient digital implementations for full-order flux observers are proposed.